Update app.py

app.py

@@ -117,15 +117,16 @@ def generate_voice_response(text, simulate=False):
         st.error(f"Error generating voice response: {e}")
         return None
 
+
 def extract_invoice_data(image_file):
     """
-    Extract financial data from invoices using Gemini Pro
+    Extract financial data from invoices using Gemini flash
     
     Args:
         image_file: Uploaded image file from Streamlit
     
     Returns:
-        Dictionary of extracted financial information
+        Extracted text information
     """
     try:
         # Initialize Gemini
@@ -145,38 +146,35 @@ def extract_invoice_data(image_file):
         img_byte_arr = img_byte_arr.getvalue()
         
         # Prepare the model
-        model = genai.GenerativeModel('gemini-1.5-pro')
+        model = genai.GenerativeModel('gemini-2.0-flash')
         
-        # Prompt for detailed invoice extraction
+        # Comprehensive prompt for invoice extraction
         prompt = """
-         Extract financial information from this invoice in a structured format:
-        
-        Provide details in a CSV-friendly format with these columns:
-        - Date
-        - Vendor
-        - Description
-        - Quantity
-        - Unit Price
-        - Total Amount
-        - Tax
-        - Payment Terms
-
-        Be precise and extract as much structured data as possible.
-        Separate multiple line items if applicable.
-        Use clear, consistent formatting.
+        Carefully extract all financial and relevant information from this invoice:
+        
+        Please provide a detailed, structured text output that includes:
+        - Complete invoice details
+        - Vendor/Company information
+        - Line items or services
+        - Total amounts
+        - Tax details
+        - Payment terms
+        - Any other significant financial information
+
+        Format the output clearly and comprehensively, making it easy to read and understand.
         """
         
         # Generate response
         response = model.generate_content([prompt, image])
-
-        
         
         # Return the extracted text
-        return parse_invoice_text_to_dataframe(response.text)
+        return response.text
     
     except Exception as e:
         st.error(f"Error extracting invoice data: {e}")
-        return None              
+        return None
+
+              
     
 # Utility Functions
 def switch_page(page_name):
@@ -580,77 +578,44 @@ def render_financial_dashboard():
 
 
 
-def parse_invoice_text_to_dataframe(text):
-    """
-    Convert extracted text to a structured DataFrame
-    
-    Args:
-        text (str): Extracted invoice text
-    
-    Returns:
-        pandas.DataFrame: Structured invoice data
-    """
-    try:
-        # Split the text into lines
-        lines = text.split('\n')
-        
-        # Prepare lists to store data
-        data = []
-        
-        # Try to parse the lines
-        for line in lines:
-            # Basic parsing - you might need to adjust regex based on invoice formats
-            match = re.match(r'(.+?)\s*,\s*(.+?)\s*,\s*(.+?)\s*,\s*(\d+)\s*,\s*(\$?\d+\.?\d*)\s*,\s*(\$?\d+\.?\d*)\s*,\s*(\$?\d+\.?\d*)\s*,\s*(.+)', line)
-            
-            if match:
-                data.append({
-                    'Date': match.group(1),
-                    'Vendor': match.group(2),
-                    'Description': match.group(3),
-                    'Quantity': match.group(4),
-                    'Unit Price': match.group(5),
-                    'Total Amount': match.group(6),
-                    'Tax': match.group(7),
-                    'Payment Terms': match.group(8)
-                })
-        
-        # Create DataFrame
-        df = pd.DataFrame(data)
-        return df
-    
-    except Exception as e:
-        st.error(f"Error parsing invoice text: {e}")
-        return pd.DataFrame()
 
 def render_invoice_processor():
+    """Render the invoice processing page"""
     st.markdown("<h1 class='main-header'>Invoice Data Extractor</h1>", unsafe_allow_html=True)
     st.markdown("<p class='sub-header'>AI-powered financial data extraction</p>", unsafe_allow_html=True)
     
+    # File uploader for invoices
     uploaded_file = st.file_uploader("Upload Invoice Image", type=['png', 'jpg', 'jpeg', 'pdf'])
     
     if uploaded_file is not None:
-        st.image(uploaded_file, caption="Uploaded Invoice", use_container_width=True)
+        # Display the uploaded image
+        st.image(uploaded_file, caption="Uploaded Invoice", use_column_width=True)
         
+        # Extract invoice data
         if st.button("Extract Invoice Details"):
             with st.spinner("Extracting invoice information..."):
-                invoice_df = extract_invoice_data(uploaded_file)
+                invoice_data = extract_invoice_data(uploaded_file)
             
-            if invoice_df is not None and not invoice_df.empty:
+            if invoice_data:
+                # Display extracted data in a formatted, readable way
                 st.subheader("Extracted Invoice Information")
-                st.dataframe(invoice_df)
+                st.markdown("<div class='advisor-card'>", unsafe_allow_html=True)
+                st.markdown("<span class='ai-badge'>AI Invoice Extraction</span>", unsafe_allow_html=True)
+                
+                # Use st.text to preserve formatting
+                st.text(invoice_data)
                 
-                # Download as CSV
-                csv = invoice_df.to_csv(index=False)
+                # Optional: Copy to clipboard
                 st.download_button(
-                    label="Download Invoice Data as CSV",
-                    data=csv,
-                    file_name="invoice_details.csv",
-                    mime="text/csv",
-                    key="download-csv"
+                    label="Copy Invoice Details",
+                    data=invoice_data,
+                    file_name="invoice_details.txt",
+                    mime="text/plain"
                 )
+                
+                st.markdown("</div>", unsafe_allow_html=True)
             else:
                 st.error("Could not extract invoice data")
-